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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Hotspot Avoidance for P2P Streaming Distribution Application: A Game Theoretic Approach
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Hotspot Avoidance for P2P Streaming Distribution Application: A Game Theoretic Approach

机译：P2P流分发应用中避免热点的博弈论方法

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摘要

Today's peer-to-peer (P2P) streaming application periodically suffers from routing hotspots, which are also known as flash crowds. A routing hotspot is typically created by an unanticipated new event that triggers an unanticipated surge of users to request streaming service from some particular peers, temporarily overwhelming the peer's delivery capabilities. In this paper, we propose novel methods that avoid routing hotspots proactively, that is, prior to a congestion event. More specifically, we define an incentive-compatible pricing vector explicitly and show that the hotspot can be avoided if all nodes in the network follow the incentive-compatible pricing policy. In order to apply this mechanism to the P2P streaming distribution applications, we propose an adaptive algorithm for distributed computation of the incentive-compatible pricing vector. The simulation results show that the incentive-compatible pricing mechanism can avoid the routing hotspot effectively.
机译：当今的点对点（P2P）流应用程序定期遭受路由热点的困扰，这些热点也称为闪存人群。路由热点通常是由意外的新事件创建的，该事件触发意外的用户激增，以请求来自某些特定对等方的流服务，从而暂时压倒了对等方的传递功能。在本文中，我们提出了一种新颖的方法，可以避免在拥塞事件发生之前主动路由热点。更具体地说，我们明确定义了激励兼容定价向量，并表明如果网络中的所有节点都遵循激励兼容定价策略，则可以避免热点。为了将此机制应用于P2P流媒体分发应用程序，我们提出了一种用于激励兼容定价向量的分布式计算的自适应算法。仿真结果表明，激励兼容定价机制可以有效地避免路由热点。

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